The Impact of Global Economic Policy Uncertainty on Investment Portfolio Diversification and Risk Management

Posted: May 13, 2021

• Zoey Martin
• Henry Baker
• Abigail Carter

Abstract

This research introduces a novel computational framework that integrates economic policy uncertainty (EPU) metrics with machine learning algorithms to enhance investment portfolio diversification and risk management strategies. Traditional portfolio optimization approaches have largely treated economic policy uncertainty as an exogenous factor or have relied on simplified volatility measures. Our methodology represents a significant departure by developing a dynamic uncertainty quantification system that processes real-time policy announcements, central bank communications, and legislative developments across major economies. We employ natural language processing techniques to extract policy uncertainty indicators from unstructured textual data, including government publications, parliamentary proceedings, and central bank statements. These indicators are then integrated into a hybrid optimization model that combines conventional mean-variance analysis with reinforcement learning algorithms capable of adapting to shifting policy environments. Our results demonstrate that portfolios constructed using our EPU-aware framework achieved superior risk-adjusted returns during periods of heightened policy uncertainty, particularly during the 2020-2023 global economic turbulence. The model successfully identified previously overlooked diversification opportunities in emerging market assets and alternative investments that exhibited lower sensitivity to policy shocks. Furthermore, our approach revealed that the conventional wisdom regarding safe-haven assets requires substantial revision in the contemporary policy landscape, with traditional hedges like government bonds showing increased vulnerability to certain types of policy uncertainty. This research contributes to both computational finance and economic policy analysis by providing a quantitatively rigorous methodology for incorporating complex policy dynamics into investment decision-making processes.